Alcaín, EduardoMuñoz Montalvo, Ana IsabelSchiavi, EmanueleS. Montemayor, Antonio2023-12-042023-12-042023-12Alcaín, E., Muñoz, A.I., Schiavi, E. et al. A non-smooth non-local variational approach to saliency detection in real time. J Real-Time Image Proc 18, 739–750 (2021). https://doi.org/10.1007/s11554-020-01016-41861-8200https://hdl.handle.net/10115/26897In this paper, we propose and solve numerically a general non-smooth, non-local variational model to tackle the saliency detection problem in natural images. In order to overcome the typical drawback of the non-local methods in image processing, which mainly is the inherent computational complexity of non-local calculus, as the non-local derivatives are computed w.r.t every point of the domain, we propose a diferent scenario. We present a novel convex energy minimization problem in the feature space, which is eficiently solved by means of a non-local primal-dual method. Several implementations and discussions are presented taking care of the computing platforms, CPU and GPU, achieving up to 33 fps and 62 fps respectively for 300×400 image resolution, making the method eligible for real time applications.engPost-prints are subject to Springer Nature re-use termsVariational methods, Convex analysis, Primal-dual, Non-local image processing, Saliency segmentation, GPU, Superpixelsinfo:eu-repo/semantics/article10.1007/s11554-020-01016-4info:eu-repo/semantics/openAccess